OP0222 IDENTIFICATION OF CAUSAL GENES AND MECHANISMS BY WHICH GENETIC VARIATION MEDIATES JUVENILE IDIOPATHIC ARTHRITIS SUSCEPTIBILITY USING FUNCTIONAL GENOMICS AND CRISPR-CAS9
Authors: A. Frantzesko, V. Malysheva, C. Shi, J. Ding, J. Bowes, W. Thomson, S. Eyre, M. Spivakov, G. Orozco
Journal: Annals of the Rheumatic Diseases (2022)

Background We recently performed the largest juvenile idiopathic arthritis (JIA) genome-wide association study (GWAS) to date 1 . Disease-associated loci contain multiple single nucleotide polymorphism (SNPs), and the majority map to non-coding enhancers, making it challenging to define causal variants and genes. Functional genomics datasets in disease-relevant tissues have shown to be essential for the functional interpretation of GWAS loci. In particular, capture Hi-C (CHi-C) has been successful in detecting chromosomal interactions linking GWAS loci to their target genes. However, such datasets are lacking in JIA. Objectives The aim of this study is to bridge this gap and advance the knowledge of the biological mechanisms that underpin susceptibility to JIA, by integrating GWAS with public epigenomics datasets and in-house generated CHi-C from JIA patients. We focus on CD4+ T-cells, which have been shown to be one of the most relevant cell types in JIA. In addition, we use CRISPR-Cas9 to validate the regulatory effect of prioritised variants on their predicted target genes. Methods Credible SNP sets for the top JIA risk loci (P &lt; 5x10 -6 ) were annotated using EpiMap data 2 . Low input whole genome promoter CHi-C (PCHi-C) was performed on CD4+ T-cells isolated from blood from 3 JIA oligoarthritis patients, and data was analysed using CHiCAGO 3 . GWAS and PCHi-C data were combined to prioritise causal genes using the Capture Hi-C Omnibus Gene Score (COGS) pipeline 4 . We subsequently employed CRISPR activation (CRISPRa) and CRISPR interference (CRISPRi) in Jurkats to assess whether prioritized JIA variants were capable of regulating the expression of the interacting genes. Results 614 credible SNPs (out of 735) were found to overlap active enhancers in CD4+ T-cells, and were prioritized for further analysis. We identified numerous significant chromatin interactions in 19 out of 44 non-MHC JIA associated loci, linking JIA SNPs mapping to T-cell enhancers to a total of 61 target genes and revealing potential novel disease pathways. Moreover, COGS prioritised a total of 7 genes ( RGS14 , ERAP2 , HIPK1 , CCR4 , CCRL2 , CCR2 , CCR3 ). A JIA associated locus on chromosome 3 contains 39 SNPs. It maps to an intergenic region and the causal gene/s are unclear. Our PCHi-C data revealed that this JIA locus presents chromatin interactions with the promoters of several genes, such as CCRL2 , CCR2 , CCR3 and CCR5 , three of which were prioritised by COGS. Two variants were selected for further analysis: rs79815064, which had the highest posterior probability, and rs8005404,the only variant within a CD4+ T-cell enhancer linked to surrounding gene activity. When both SNPs were targeted with CRISPRa and CRISPRi, we observed an increased and decreased expression, respectively, of CCRL2 , CCR2 , CCR3 and CCR5, confirming their role in disease. These genes belong to the chemokine receptor family and are important regulators of the inflammatory response. Conclusion Our work shows how functional genomics can help identify biological mechanisms by which GWAS variants increase risk of JIA, which in turn will benefit patients through personalised medicine and the identification of therapeutic targets. References [1]López-Isac, E. et al. Combined genetic analysis of juvenile idiopathic arthritis clinical subtypes identifies novel risk loci, target genes and key regulatory mechanisms. Ann. Rheum. Dis. 80 , 321–328 (2021). [2]Boix, C. A., James, B. T., Park, Y. P., Meuleman, W. &amp; Kellis, M. Regulatory genomic circuitry of human disease loci by integrative epigenomics. Nat. 2021 5907845 590 , 300–307 (2021). [3]Cairns, J. et al. CHiCAGO: Robust detection of DNA looping interactions in Capture Hi-C data. Genome Biol. 17 , 1–17 (2016). [4]Javierre, B. M. et al. Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters. Cell 167 , 1369 (2016). Disclosure of Interests Antonio Frantzesko: None declared, Valeriya Malysheva: None declared, Chenfu Shi: None declared, James Ding: None declared, John Bowes: None declared, Wendy Thomson: None declared, Stephen Eyre: None declared, Mikhail Spivakov Shareholder of: co-founder and shareholder of Enhanc3D Genomics Ltd, Gisela Orozco: None declared